<![CDATA[The climate crisis and the financing deficit for the Sustainable Development Goals (SDGs) are two interrelated existential threats. The OECD (2025) notes that the SDG financing gap has surged 60% to USD 4 trillion annually, while global climate finance needs reach USD 6.4 trillion annually by 2030. Paradoxically, the world's waqf assets, estimated at USD 1 trillion annually, are largely idle and unproductive due to weak management and a lack of management technology. This study integrates Artificial Intelligence (AI) with abandoned waqf assets to create an ethical, scalable, and sustainable climate finance mechanism. Using a PRISMA protocol-based Systematic Literature Review of 50 scholarly sources (2023–2026) analyzed thematically and bibliometrically, the study identifies four critical gaps: the absence of an integrated AI–waqf–climate finance–SDGs model; the absence of a machine learning-based Social Return on Waqf Investment (SROWI) metric; The absence of an AI-based inventory system for idle waqf assets; and the lack of integration of Islamic Social Finance Theory with the Resource-Based View. In response, this study proposes the Climate Waqf Intelligence Framework (CWIF), an original four-layer conceptual framework—asset mapping (Computer Vision/GIS), climate project intelligence (ESG-SDGs-based ML), impact forecasting (Deep Learning LSTM), and SROWI measurement (NLP)—based on a synthesis of the three theories and principles of Maqasid al-Shariah. Its contributions are both theoretical and practical through policy recommendations for BWI, the Financial Services Authority (OJK), and relevant ministries.]]>
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